Leveraging Data to Improve the Quality of Patient Care

Data
is the asset that needs ongoing optimization. Especially so in the healthcare service
space. Care delivery organizationsare no longer constrained by a shortage of
data for quality patient care. In fact, there is so much data available with healthcare organizations
today, that managing and leveraging this data to its full potential has become
a challenge.

Natural Language Processing, an element of Artificial Intelligence, is
helping care services providers to analyze and use a host of data that lies in
repositories. This is information collected from disparate sources such as
patient portals, EHRs, EMRs, and so on.

Healthcare
analytics, that leverages all this data, promises to reduce the cost of care,
improve outcomes, and enhance the patient experience.

These
factors come together up to improve the overall quality of patient care- a
tremendous opportunity for healthcare organizations to retain patients and gain
a competitive edge.

Health Care Services Shift from Volume Care to Value-based Care

For
so long, the healthcare service industry has been less than engagedwith its customers-
the patients. But times are changing rapidly. Healthcare organizations now
realize they have to deliver better outcomes to stay in business.

We
are witnessing a dynamic shift from the traditional fee-for-service model to
value and outcome-based healthcare delivery.

Value-based
healthcare services requires practitioners to implement healthcare analytics at the
point of delivery to evaluate the performance and effectiveness of care. With
performance assessments and health data related to patient recovery, analytics
can be used to provide ongoing feedback to care practitioners.

How Data Propels Quality Patient Care

Here
are a few simple and subtle applications of analytics in advancing the quality
of care delivery-

Patient
Predictions for Improved Staffing
– A Forbes article details how four hospitals are using data from a
variety of sources to predict patient influx and then optimize staffing. One of
the key datasets these hospitals use is a decade’s data on hospital admissions.
Optimum staffing is the backbone of care quality in healthcare organizations.
If you put too many workers, you increase unnecessary costs. Too few workers
can mean poor service delivery.

Electronic Health
Records – The most
popular application of Big Data in healthcare is the use of EHRs. These portals
capture patient data in the form of their medical history, demographics,
allergies, and so on. EHRs streamline the initial discovery process for
healthcare organizations by making all of a patient’s health background
available to doctors and specialists at a glance. Subsequently, this data is
utilized to predict patient health, plan care delivery, and optimize outcomes.

Strategic Care
Planning – Healthcare data
can also allow physicians insights into what motivates patients to complete
their treatment. Care managers can analyze people in different demographics and
learn what motivates them to stay healthy. By using these motivators for each
patient, care practitioners can enhance outcomes and carry out strategic care
planning.

Predictive
Analytics in Healthcare – Healthcare
business intelligence can allow physicians to use data and analytics to drive intelligent
decision-making that delivers better patient care. This is particularly useful
in cases of complex medical histories or multiple conditions. New tools would
predict if patients are prone to diabetes or heart illnesses and help
practitioners weigh those factors into their decisions. This ultimately
improves the quality of care delivery ad accelerates outcomes.

Coordinated Care – Care coordination allows integrated team
members to track patient’s significant events, care activities, and
appointments. After analyzing patient data, care providers can create a
personalized experience for each patient- taking into account their sleep
times, diet, activities, and other factors. Patient interactions can be
recorded for future use and physicians can create a customized care plan with
the patient’s healthcare outcome and goal in mind.

Reduced Care
Costs – Outcome and value-based care incentivize
delivering performance in healthcare. Instead of focusing on the reimbursement
on a case-by-case basis, overall outcomes determine costs. Interconnected EHRs
can provide detailed information to help cut costs by reducing redundant or
unnecessary care. By identifying patterns in a population, prescriptive
analytics can estimate the cost of care for an individual- allowing
organizations to direct care delivery to reduce waste and improve care
efficiency.

Fewer ER Visits
and Shorter Length of Stay – One of the
chronic issues in healthcare is the crowding of emergency rooms- which often
leads to fatal conditions for patients waiting for their turn. With analytics
and insights into patient health history, doctors can instantly learn if a
patient underwent certain tests recently, what advice they were given the last
time, if they already have access to a care manager at another facility, and so
on. By optimizing the influx of patients at ERs, the quality of care can
drastically improve.

The
application of Big Data and Analytics in healthcare could open avenues to
dramatically improve the patient experience, the quality of care, and patient
satisfaction.

Stay Relevant, Deliver Outcomes

With
an aging population, there is an increasing demand for expensive, critical
care. But this is also transforming how healthcare companies operate.

Healthcare services
is movingtowards an outcome-based model. Organizations are now expected to be
transparent and accountable. All of that plays a role in the need for improved
efficiency in care delivery. And, data and analytics have an important seat at
the table here.

Healthcare service
organizations have made tremendous investments in infrastructure. The time now
is to cash in and focus on improving care. The key here is to use the assets
currently available. One of which is the data available with the industry-
thanks to EHRs, integrated care portals, and data captured at the point of
delivery.

To
do this, providers will have to make excellent operational decisions by
leveraging predictive analytics. They will need to deliver prescriptive
recommendations throughout the system to clinical and administrative drivers.
In this digital age,
where customer know exactly what they want and are ready to demandjust that,
what other option do healthcare organizations have than to deliver improved
care quality?